A general non-linear index of association between two continuous rank-order variables
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Non-linear dependence between two continuous variables has been given but little consideration among statisticians to this day, and no correlation index has been contrived, apart from the semi-categorized 2 coefficient in the anova context. Here, a non-parametric, rank-based approach is implemented, giving rise to two coefficients, RY, which measures the non-linear (and non-monotonic) variation of the Y series concomitant to the X series, and RXY, a symmetrised measure of the non-linear correspondence between the two series. The gist of the approach resides in the postulate that, if the series are related in any manner, numerically consecutive values of one variable should be linked to values of the other variable having reduced mutual differences. RY and RXY are presented here, with their first moments and sets of exact and approximate critical values, and they are the distribution-free counterparts of coefficients A and AS (Laurencelle, 2012) formerly presented for the normal parametric context.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it